CN113342605B - PostgreSQL database monitoring and traceability analysis method and system - Google Patents
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 55
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- 239000011800 void material Substances 0.000 claims abstract description 35
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
- G06F16/2433—Query languages
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- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
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- G06F9/44521—Dynamic linking or loading; Link editing at or after load time, e.g. Java class loading
- G06F9/44526—Plug-ins; Add-ons
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
- G06F9/5016—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals the resource being the memory
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Abstract
The embodiment of the invention provides a processing method and a system for constructing a PostgreSQL database by a snapshot sampling technology, wherein the method comprises the following steps: synchronously loading a monitoring plug-in when a database is started by using a hook, requesting memory allocation from a database main process, and creating a monitoring sub-process; after the monitoring subprocess is started, database parameters are obtained, wherein the database parameters comprise: database state, sql statements, execution plans, lock information, data block changes, host system information; real-time shooting a database snapshot through real-time monitoring of sql sentences of database operation and the running state of the database; and (3) storing the database snapshot shot in real time into a corresponding table and view by calling a snapshot_w (void) function.
Description
Technical Field
The invention belongs to the technical field of information, and particularly relates to a method and a system for constructing PostgreSQL database monitoring and traceability analysis based on database snapshot sampling storage.
Background
In daily operation and maintenance of the database, diagnosis of database performance, performance optimization and fault tracing are an important ring in daily operation and maintenance work. ASH (Active Session History) exists in Oracle, and ASH provides the most direct and effective basis for analyzing performance problems at the latest moment by extracting active session samples every second. However, in PostgreSQL, performance problems generally occur, and can only be observed through the combination of the self-contained performance view pg_stat_activity of the system and commands such as top and iostat of the operating system layer, and the biggest defect is that the pg_stat_activity view can only see the currently running Postgres process state, only a snapshot of the time point, only the running state of the database at the moment, and no ability to locate performance problems in historical running is available.
Disclosure of Invention
Aiming at the problem that the historical running state cannot be checked in the prior art, the invention aims to provide a method and a system for constructing PostgreSQL database monitoring and traceability analysis based on database snapshot sampling storage so as to improve the database operation and maintenance efficiency and usability.
In order to solve the above problems, an embodiment of the present invention provides a method for constructing PostgreSQL database monitoring and traceability analysis based on snapshot sampling technology, including:
synchronously loading a monitoring plug-in when a database is started by using a hook through a hook_proc (void) function, requesting memory allocation from a database main process postgres through a proc_entry_memsize (void) function method call, and finally creating a monitoring subprocess by using an init_proc (constraint str, int len) function;
after the monitor sub-process starts, get_ dbstatus (void), get_sql (const_str, int len), get_side_analysis (parameter_query), get_lock_info (i_mode text), get_block change (pg_function_ars), get_host_process_info (void) functions are used to obtain database parameters, where the database parameters include: database state, sql statements, execution plans, lock information, data block changes, host system information;
real-time shooting a database snapshot through real-time monitoring of sql sentences of database operation and the running state of the database; and (3) storing the database snapshot shot in real time into a corresponding table and view by calling a snapshot_w (void) function.
Further, the method further comprises:
the monitoring subprocess uses copy_stat (void) function to sample the pg_stat_statements view, but different from the original view, the monitoring subprocess additionally adds a preset field on the basis of the pg_stat_activity view to record the running state of the database; wherein the preset field includes: blockers, blockpid, blocker _state; wherein the pg_stat_statements are database self-contained plug-ins.
Further, the method further comprises:
the sampled snapshot data is stored in the pg_active_session_history view and the pg_stat_events_history view.
Further, the pg_active_session_history view and the pg_stat_systems_history view include the following fields:
further, the monitor subprocess further comprises GUC parameters for controlling the monitor subprocess to collect behaviors and frequencies, including:
pgsendinel_ash. Sampling_period: sampling period, defaulting to 1s;
pgsendinel_ash.max_entries: the size of the buffer area of the pg_active_session_history view in the memory is defaulted to 1000;
pgsentinel_pgssh.max_entries: the size of the buffer in the memory of the pg_stat_systems_history view defaults to 1000;
pgsendinel. Db_name: the database to be monitored is postgres by default;
pgsendinel_ash_track_idle_trans: tracking a session in the state of an idle transaction, wherein the default is false;
pgsendtinel_pgssh. Whether the monitoring subprocess is started to sample the snapshot is defaulted to false.
Meanwhile, the embodiment of the disclosure also provides a system for constructing a PostgreSQL database monitoring and traceability analysis based on a snapshot sampling technology, which comprises the following steps:
the system comprises a building module, a monitoring module and a control module, wherein the building module is used for synchronously loading a monitoring plug-in when a database is started by using a hook through a hook-proc (void) function, requesting memory allocation from a database main process postgres through a proc-entry-memsize (void) function method call, and finally creating a monitoring subprocess by using an init-proc (constraint str, int len) function;
a starting module, configured to obtain database parameters using a get_ dbstatus (void), get_sql (const char str, int len), get_parameter_analysis (parameter_pstate, query_query), get_lock_info (i_mode text), get_block change (pg_function_args), get_host_procs_info (void) function after the monitor sub-process starts, where the database parameters include: database state, sql statements, execution plans, lock information, data block changes, host system information;
the snapshot module is used for shooting the database snapshot in real time through the sql statement and the database running state of the real-time monitoring database operation; and (3) storing the database snapshot shot in real time into a corresponding table and view by calling a snapshot_w (void) function.
The technical scheme of the invention has the following beneficial effects: according to the technical scheme, the real-time state of the database can be sampled based on the snapshot, and the database can be operated at the database node in a non-invasive kernel mode; and the real-time running state of the database is stored as a snapshot by setting the acquisition frequency and the acquisition range, so that the historical running condition of the database can be traced. The technical scheme is realized based on the built-in api and the expansion mechanism of the database, does not invade the kernel, and has strong safety and flexibility.
Drawings
Fig. 1 is a system logic flow diagram of an embodiment of the present disclosure.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The present invention will be described in further detail with reference to the accompanying drawings, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The method of post-evaluation is further described below with reference to the accompanying drawings.
As shown in fig. 1, an embodiment of the present disclosure proposes a method for constructing PostgreSQL database monitoring and traceability analysis based on snapshot sampling technology, including:
the method comprises the steps that a program is synchronously loaded when a database is started by a hook through a hook_proc (void) function, memory allocation is requested from a database main process postgres through a proc_entry_memsize (void) function method call, and finally an init_proc (constraint_str, int len) function is used for creating a monitoring subprocess;
after the monitor subprocess is started, using a series of functions of get_ dbstatus (void), get_sql (const_str, int len), get_side_analysis (parameter_pstate, query) get_lock_info (i_mode text), get_block change (pg_function_args), get_host_process_info (void), and the like, obtaining data such as a database, sql statement, execution plan, lock information, data block change, host system information, and the like, adding and deleting sql statement and database running state through the real-time monitor database, and capturing a snapshot of the database in real time by calling a snapshot_w (void) function into a correlation table and a view.
Meanwhile, in order to acquire more fine-grained queries, the monitoring subprocess also uses copy_stat (void) to sample the pg_stat_states view, but different from the original view, the monitoring subprocess additionally adds some fields on the basis of the pg_stat_activity view, so as to conveniently record more detailed database running states, such as blockers, blockpid, blocker _state and other fields. Wherein pg_stat_statements are database self-contained plug-ins providing a rough historical sql running record.
The sampled snapshot data is queried and revealed by reading the pg_active_session_history view and the pg_stat_systems_history view. The pg_active_session_history and pg_stat_systems_history may be as shown in table 1 below:
TABLE 1
Further, the system also comprises GUC parameters for controlling the functions of monitoring the sub-process acquisition behaviors, frequency and the like, and the total of the GUC parameters is as follows:
pgsendinel_ash. Sampling_period: sampling period, defaulting to 1s;
pgsendinel_ash.max_entries: the size of the buffer area of the pg_active_session_history view in the memory is defaulted to 1000;
pgsentinel_pgssh.max_entries: the size of the buffer in the memory of the pg_stat_systems_history view defaults to 1000;
pgsendinel. Db_name: the database to be monitored is postgres by default;
pgsendinel_ash_track_idle_trans: tracking a session in the state of an idle transaction, wherein the default is false;
pgsendtinel_pgssh. Whether the monitoring subprocess is started to sample the snapshot is defaulted to false.
The invention will be further illustrated by the following specific examples.
Step one, the procedure for implementing the method of the embodiment of the present invention (hereinafter referred to as pgsentinel) is based on relying on PostgreSQL database (version need not less than 9.6), so PostgreSQL needs to be installed first.
Step two, uploading the program source code, then decompressing and installing, and then executing the following steps.
export PATH＝/app/pg/122/bin:$PATH:
make&&make install
Step three, configuring pgsentinel according to the embodiment of the invention
Edit/pgdata/data/postgresql. Conf file, in which parameters are set:
shared_preload_libraries＝'pg_stat_statements,pgsentinel'
track_activity_query_size＝2048
pg_stat_statements.track＝all
pgsentinel_pgssh.enable＝true
step four, starting the database and starting and creating the pgsentinel process
pgsentinel needs to be started first in a required monitoring database, a corresponding monitoring view is created after starting, and the program depends on pg-stat_states, so synchronous starting is also required, and the process is completed by a createextension command:
pg_ctlstart-D/pgdata/data
createextension pg_stat_statements
createextensionpgsentinel。
and fifthly, performing snapshot sampling and storage on the database operation sql and the state after the monitoring subprocess is operated in the background. The database can then view the snapshot sample data in the view after executing some sql.
Finally, by carrying out the association query on the snapshot information sampled by the embodiment of the invention, more practical performance analysis can be obtained, for example:
1. top 10SQL for obtaining the most consumed CPU
2. Acquiring top 10 average active session AAS (Average Active Sessions)
3. Acquiring top 10 wait for event
4. Get Top 10 wait SQL
5. Querying load distribution
select backend_type,count(*)/(select count(distinct ash_time)::float from
pg_active_session_history)as load
from pg_active_session_historygroup by backend_type；
Meanwhile, the embodiment of the disclosure also provides a system for constructing a PostgreSQL database monitoring and traceability analysis based on a snapshot sampling technology, which comprises the following steps:
the system comprises a building module, a monitoring module and a control module, wherein the building module is used for synchronously loading a monitoring plug-in when a database is started by using a hook through a hook-proc (void) function, requesting memory allocation from a database main process postgres through a proc-entry-memsize (void) function method call, and finally creating a monitoring subprocess by using an init-proc (constraint str, int len) function;
a starting module, configured to obtain database parameters using a get_ dbstatus (void), get_sql (const char str, int len), get_parameter_analysis (parameter_pstate, query_query), get_lock_info (i_mode text), get_block change (pg_function_args), get_host_procs_info (void) function after the monitor sub-process starts, where the database parameters include: database state, sql statements, execution plans, lock information, data block changes, host system information;
the snapshot module is used for shooting the database snapshot in real time through the sql statement and the database running state of the real-time monitoring database operation; and (3) storing the database snapshot shot in real time into a corresponding table and view by calling a snapshot_w (void) function.
Of course, the above system corresponds to the above method, and will not be described herein.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the present invention.
Claims (4)
1. A method for PostgreSQL database monitoring and traceability analysis, comprising:
synchronously loading a monitoring plug-in when a database is started by using a hook through a hook_proc (void) function, requesting memory allocation from a database main process postgres through a proc_entry_memsize (void) function method call, and finally creating a monitoring subprocess by using an init_proc (constraint str, int len) function;
after the monitor sub-process starts, get_ dbstatus (void), get_sql (const_str, int len), get_side_analysis (parameter_query), get_lock_info (i_mode text), get_block change (pg_function_ars), and get_host_processes_info (void) functions are used to obtain database parameters, where the database parameters include: database state, sql statements, execution plans, lock information, data block changes, and host system information;
real-time shooting a database snapshot through real-time monitoring of sql sentences of database operation and the running state of the database; storing the database snapshot shot in real time into a corresponding table and view by calling a snapshot_w (void) function;
the monitoring subprocess uses copy_stat (void) function to sample the pg_stat_statements view, but different from the original view, the monitoring subprocess additionally adds a preset field on the basis of the pg_stat_activity view to record the running state of the database; wherein the preset field includes: blockers, blockpid and blocker_state; wherein the pg_stat_statements are database self-contained plug-ins;
the monitoring subprocess also comprises GUC parameters for controlling the acquisition behavior and frequency of the monitoring subprocess, and the GUC parameters comprise:
pgsendinel_ash. Sampling_period: sampling period, defaulting to 1s;
pgsendinel_ash.max_entries: the size of the buffer area of the pg_active_session_history view in the memory is defaulted to 1000;
pgsentinel_pgssh.max_entries: the size of the buffer in the memory of the pg_stat_systems_history view defaults to 1000;
pgsendinel. Db_name: the database to be monitored is postgres by default;
pgsendinel_ash_track_idle_trans: tracking a session in the state of an idle transaction, wherein the default is false;
pgsendtinel_pgssh. Whether the monitoring subprocess is started to sample the snapshot is defaulted to false.
2. The method of PostgreSQL database monitoring and traceability analysis of claim 1, further comprising:
the sampled snapshot data is stored in the pg_active_session_history view and the pg_stat_events_history view.
3. The method of PostgreSQL database monitoring and trace-source analysis of claim 2, wherein the pg_active_session_history view and pg_stat_events_history view comprise the following fields:
4. a PostgreSQL database monitoring and traceability analysis system, comprising:
the system comprises a building module, a monitoring module and a control module, wherein the building module is used for synchronously loading a monitoring plug-in when a database is started by using a hook through a hook-proc (void) function, requesting memory allocation from a database main process postgres through a proc-entry-memsize (void) function method call, and finally creating a monitoring subprocess by using an init-proc (constraint str, int len) function;
a starting module, configured to obtain database parameters using get_ dbstatus (void), get_sql (const_str, int len), get_parameter_analysis (parameter_pstate, query_query), get_lock_info (i_mode text), get_block change (pg_function_args), and get_host_proc_info (void) functions after the monitor sub-process starts, where the database parameters include: database state, sql statements, execution plans, lock information, data block changes, and host system information;
the snapshot module is used for shooting the database snapshot in real time through the sql statement and the database running state of the real-time monitoring database operation; storing the database snapshot shot in real time into a corresponding table and view by calling a snapshot_w (void) function;
the monitoring subprocess uses copy_stat (void) function to sample the pg_stat_statements view, but different from the original view, the monitoring subprocess additionally adds a preset field on the basis of the pg_stat_activity view to record the running state of the database; wherein the preset field includes: blockers, blockpid and blocker_state; wherein the pg_stat_statements are database self-contained plug-ins; the monitoring subprocess also comprises GUC parameters for controlling the acquisition behavior and frequency of the monitoring subprocess, and the GUC parameters comprise:
pgsendinel_ash. Sampling_period: sampling period, defaulting to 1s;
pgsendinel_ash.max_entries: the size of the buffer area of the pg_active_session_history view in the memory is defaulted to 1000;
pgsentinel_pgssh.max_entries: the size of the buffer in the memory of the pg_stat_systems_history view defaults to 1000;
pgsendinel. Db_name: the database to be monitored is postgres by default;
pgsendinel_ash_track_idle_trans: tracking a session in the state of an idle transaction, wherein the default is false;
pgsendtinel_pgssh. Whether the monitoring subprocess is started to sample the snapshot is defaulted to false.
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